Conventionally, there is an abnormal detection apparatus detecting an abnormality of a robot used for Factory Automation work such as assembly work or the like. By the abnormal detection apparatus, the abnormality of the robot is detected, and by specification of the cause, measure, improvement or the like, it is possible to perform efficient Factory Automation work, for example.
In the abnormal detection apparatus, there is a case of detecting the abnormality by imaging the work of an objective robot by using a camera or the like and performing image processing to the imaged image data. For example, there is a following abnormal detection apparatus. Namely, the abnormality apparatus extracts feature data (or moving image feature, which may hereafter be referred to as “moving image feature”) from a plurality of image frames by allowing the robot to carry out normal work, and generates a normal space data including a plurality of feature data. And, the abnormal detection apparatus compares the normal space data with the moving image feature extracting by operation work of the robot and calculates abnormal measure. The abnormal detection apparatus notifies the abnormality by an alarm or like when the calculated abnormal measure exceeds a set value.
There is a case that a number of dimensions of the moving image feature (for example, a number of a type of the moving image feature) is a few hundred, and the abnormal detection apparatus can acquire the moving image feature efficiently by reducing the number of dimensions by a technique of Principal Component Analysis (PCA) or like. To reduce the number of dimensions may hereinafter be referred to as “contraction”, for example. For example, by causing the robot to carry out real work being equal or higher than the number of dimensions of the moving image feature, the abnormal detection apparatus can perform contraction of the number of dimensions of the moving image feature efficiently. Therefore, when the number of dimensions of the moving image feature is a few hundred, there is a case that the abnormal detection apparatus acquires image data by causing the robot to perform the work repeatedly at hundreds of time.
Such techniques related to image processing include techniques as follows, for example. Namely, there is an image processing apparatus that performs N times of geometric transformations to model pattern, generates a transformation model pattern indicating appearance of an object of relative posture in three-dimensionally different with respect to standard relative posture, and performs pattern matching by using the transformation model pattern to the image data. According to the above techniques, it is urged that the object whose position and posture are not fixed can be detected and its three-dimensionally position and/or two-dimensionally posture can be recognized.
Further, there is a motion editing apparatus for a robot, which changes a position and inclination of each body part of a model of the robot in three-dimensional pseudo space, calculates an angle of each joint of the robot, generates key frame data, and outputs the generated key frame data to an articulated robot. It is urged that, according to the above technique, the motion editing apparatus for the robot to generate various kinds of motion data of the robot easily can be provided.